There are an estimated half a million cases of oral and oropharyngeal cancer worldwide. [1] Oral cavity mortality rates have remained unchanged or have decreased in some countries around the world from 1995 to 2005. [2] It is well established that oral cancer incidence and mortality are higher in regions where tobacco habits, in the form of chewing and/or smoking, with or without alcohol intake, are common. [3] It is also known that oral cancer cases distribution and occurrence varies by age, ethnic group, culture and life style, and level of country development. [4] For example, the Population Attributable Risk (PAR) due to the effects of tobacco and alcohol on oral cavity cancers is lower in the United States (US) than in Europe and Latin America. [5]
While incidence and mortality rates are relatively low compared to other cancers, oral cancer patients are usually diagnosed in an advanced stage, which is associated with worse prognosis and higher radio- and chemotherapy morbidity. Moreover, the oral cavity patient quality of life is disproportionately compromised, since surgical therapy can be mutilating and often has significant effects on swallowing, speech, and physical appearance. [6] Evidently, improved oral cancer prevention, early detection, diagnostic, and clinical management tools are needed to identify high risk patients, such as patients with smoking and alcohol exposures, patients without adequate access to health care, and patients with high risk lesions such as leukoplakia, which may progress to carcinoma lesions.[7]
Quantitative Methylation Specific PCR (qMSP) has been proposed as a platform to develop early detection, diagnostic, and clinical management biomarkers in Head and Neck Squamous Cell Carcinoma (HNSCC).[8-10] However, previous efforts at identifying epigenomic biomarkers in HNSCC have been limited by candidate gene or cell culture-based discovery approaches and validation technologies on well characterized pathology specimens from homogeneous cohorts, all of which has limited the clinical relevance of the results. [11-13] Numerous genes in OSCC tissues have been studied for promoter methylation status. It has also been shown that histologically normal tissue adjacent to tumors and premalignant lesions can also have high levels of methylation of some genes, suggesting that methylation is an early event in oral carcinogenesis [14]. Hypermethylated genes in OSCC have been associated with alterations in proliferation, DNA repair, apoptosis, cell-cell adhesion and angiogenesis, Clinically, they have been associated with tumor aggressiveness, invasiveness and with the malignant transformation of oral epithelial dysplasia [14]. Recently, our lab showed that promoter hypermethylation is present in OSCC premalignant lesions, is useful for HNSCC detection and plays a role in the development of resistance to cytotoxic chemotherapeutic agents [15-18]. Other laboratories have shown that promoter methylation of genes in saliva may serve as potential biomarkers for early detection of primary and relapsing OSCC/HNSCC [19, 20].
Pharmacologic unmasking in cell lines with subsequent validation in surgical specimens has been the canonical pseudo genome-wide discovery approach used to identify differentially genes in OSCC.[21] This approach has provided a description of hypermethylated and silenced tumor suppressor genes or hypomethylated candidate proto-oncogenes, in well characterized and carefully dissected samples from, in the large part, North American patients.[22, 23] The results obtained with the pharmacologic unmasking approach in cell lines however have shown poor clinical application, probably due to pharmacologic bias and methylation changes associated to cell lines passage, as well as the high degree of cellular heterogeneity in tumor tissue and saliva samples.
The advent of high throughput genomic platforms provides the opportunity to examine novel approaches. We set out to overcome the limitations of previous methods using a novel study design in clinically defined samples from populations with different risk profiles. [24-26] We used high-density promoter methylation platforms, publicly available expression arrays, and qMSP in a Phase I Biomarker Development Trial to identify differentially methylated genes that can distinguish between OSCC/HNSCC tumor and normal tissue in study populations with different risk factors. [8, 27, 28] A novel feature of this project, which facilitates the heterogeneous risk factor approach, is the two-stage design of the study. In the first stage, called the Discovery Screen, we used clinical samples obtained from Spain, a population with high OSCC risk associated to tobacco smoking and alcohol consumption. [29, 30] In the second stage, called the “Prevalence Screen,” we analyzed the promoter methylation status of the best performing hypermethylated genes identified in the Discovery Screen on DNA isolated from a separate cohort of HNSCC tumor samples from North America with well characterized histopathology. Markers that perform well in a population with a heterogeneous risk profile in a clinical setting in the Discovery screen have a higher probability of performing well in a well-characterized set of confirmed cases and controls in the Prevalence screen. This novel study design maximizes resource investment in Phase I Biomarker Development Trials (BDT) and ensures that more robust biomarkers are tested in Phase II. Bioinformatics, biostatistical and pathway analyses were used to identify relevant genes and Quantitative Methylation Specific PCR (qMSP) was used to determine the differential methylation identified in particular genes or pathways. There is a continuing need in the art to develop sensitive and accurate detection of cancers at an early stage.